activity
20182026
most citedSegment Anything Model for Medical Image Analysis: an Experimental Study

762 citations · 833 across the 25 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

eess.IV2025

Are Vision Foundation Models Ready for Out-of-the-Box Medical Image Registration?

Hanxue Gu, Yaqian Chen, Nicholas Konz +2

Foundation models, pre-trained on large image datasets and capable of capturing rich feature representations, have recently shown potential for zero-shot image registration. Howeve…

eess.IV2025★ 2 cited

MRI-CORE: A Foundation Model for Magnetic Resonance Imaging

Haoyu Dong, Yuwen Chen, Hanxue Gu +4

The widespread use of Magnetic Resonance Imaging (MRI) in combination with deep learning shows promise for many high-impact automated diagnostic and prognostic tools. However, trai…

eess.SP2025

SegmentAnyMuscle: A universal muscle segmentation model across different locations in MRI

Roy Colglazier, Jisoo Lee, Haoyu Dong +12

The quantity and quality of muscles are increasingly recognized as important predictors of health outcomes. While MRI offers a valuable modality for such assessments, obtaining pre…

eess.IV2025

GuidedMorph: Two-Stage Deformable Registration for Breast MRI

Yaqian Chen, Hanxue Gu, Haoyu Dong +5

Accurately registering breast MR images from different time points enables the alignment of anatomical structures and tracking of tumor progression, supporting more effective breas…

eess.IV2025

Accelerating Volumetric Medical Image Annotation via Short-Long Memory SAM 2

Yuwen Chen, Zafer Yildiz, Qihang Li +5

Manual annotation of volumetric medical images, such as magnetic resonance imaging (MRI) and computed tomography (CT), is a labor-intensive and time-consuming process. Recent advan…